Matches in SemOpenAlex for { <https://semopenalex.org/work/W163118202> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W163118202 abstract "In the 20th century, genetic scientists anticipated that shortly after availability of the whole-genome profiling technologies, the patterns of complex diseases would be decoded easily. However, we recently found it extremely difficult to predict women’s susceptibility to breast cancer based on their germline genomic profiles and achieved an accuracy of 59.55% over the baseline of 51.52% after applying a wide variety of biologically-naive and biologically-informed feature selection and supervised learning methods. By contrast, in a separate study, we showed that we can utilize these genomic profiles to accurately predict ancestral origins of individuals. While there are biomedical explanations of accurate predictability of an individual’s ancestral roots and poor predictability of her susceptibility to breast cancer, my research attempts to utilize the computational learning theory framework to explain what concepts are learnable, based on the three common characteristics of biomedical datasets: the high dimensionality, the label heterogeneity, and the noise." @default.
- W163118202 created "2016-06-24" @default.
- W163118202 creator A5031498685 @default.
- W163118202 date "2013-01-01" @default.
- W163118202 modified "2023-09-27" @default.
- W163118202 title "Learning Disease Patterns from High-Throughput Genomic Profiles: Why Is It So Challenging?" @default.
- W163118202 cites W1979595209 @default.
- W163118202 cites W2016060560 @default.
- W163118202 cites W2121837006 @default.
- W163118202 cites W2787894218 @default.
- W163118202 cites W4238284510 @default.
- W163118202 cites W4238893454 @default.
- W163118202 cites W604696361 @default.
- W163118202 doi "https://doi.org/10.1007/978-3-642-38457-8_34" @default.
- W163118202 hasPublicationYear "2013" @default.
- W163118202 type Work @default.
- W163118202 sameAs 163118202 @default.
- W163118202 citedByCount "0" @default.
- W163118202 crossrefType "book-chapter" @default.
- W163118202 hasAuthorship W163118202A5031498685 @default.
- W163118202 hasConcept C104317684 @default.
- W163118202 hasConcept C111919701 @default.
- W163118202 hasConcept C119857082 @default.
- W163118202 hasConcept C121332964 @default.
- W163118202 hasConcept C121608353 @default.
- W163118202 hasConcept C141231307 @default.
- W163118202 hasConcept C148483581 @default.
- W163118202 hasConcept C154945302 @default.
- W163118202 hasConcept C187191949 @default.
- W163118202 hasConcept C189206191 @default.
- W163118202 hasConcept C197640229 @default.
- W163118202 hasConcept C41008148 @default.
- W163118202 hasConcept C530470458 @default.
- W163118202 hasConcept C54355233 @default.
- W163118202 hasConcept C62520636 @default.
- W163118202 hasConcept C86803240 @default.
- W163118202 hasConceptScore W163118202C104317684 @default.
- W163118202 hasConceptScore W163118202C111919701 @default.
- W163118202 hasConceptScore W163118202C119857082 @default.
- W163118202 hasConceptScore W163118202C121332964 @default.
- W163118202 hasConceptScore W163118202C121608353 @default.
- W163118202 hasConceptScore W163118202C141231307 @default.
- W163118202 hasConceptScore W163118202C148483581 @default.
- W163118202 hasConceptScore W163118202C154945302 @default.
- W163118202 hasConceptScore W163118202C187191949 @default.
- W163118202 hasConceptScore W163118202C189206191 @default.
- W163118202 hasConceptScore W163118202C197640229 @default.
- W163118202 hasConceptScore W163118202C41008148 @default.
- W163118202 hasConceptScore W163118202C530470458 @default.
- W163118202 hasConceptScore W163118202C54355233 @default.
- W163118202 hasConceptScore W163118202C62520636 @default.
- W163118202 hasConceptScore W163118202C86803240 @default.
- W163118202 hasLocation W1631182021 @default.
- W163118202 hasOpenAccess W163118202 @default.
- W163118202 hasPrimaryLocation W1631182021 @default.
- W163118202 hasRelatedWork W1725707671 @default.
- W163118202 hasRelatedWork W1822666083 @default.
- W163118202 hasRelatedWork W1967289357 @default.
- W163118202 hasRelatedWork W2053719406 @default.
- W163118202 hasRelatedWork W2246605701 @default.
- W163118202 hasRelatedWork W2280689192 @default.
- W163118202 hasRelatedWork W2343554498 @default.
- W163118202 hasRelatedWork W2405013394 @default.
- W163118202 hasRelatedWork W2505764255 @default.
- W163118202 hasRelatedWork W2767794035 @default.
- W163118202 hasRelatedWork W2943001064 @default.
- W163118202 hasRelatedWork W2950223732 @default.
- W163118202 hasRelatedWork W2950986310 @default.
- W163118202 hasRelatedWork W2976971063 @default.
- W163118202 hasRelatedWork W3000157488 @default.
- W163118202 hasRelatedWork W3018639694 @default.
- W163118202 hasRelatedWork W3041956550 @default.
- W163118202 hasRelatedWork W3113544273 @default.
- W163118202 hasRelatedWork W3199688452 @default.
- W163118202 hasRelatedWork W3201164482 @default.
- W163118202 isParatext "false" @default.
- W163118202 isRetracted "false" @default.
- W163118202 magId "163118202" @default.
- W163118202 workType "book-chapter" @default.